Many documents are structured using a two-dimensional (2D) layout. Some example documents may be invoices, resumes, presentations, reports, and blogs. These documents may include tables, lists, or other visual elements. Current document recognition methods typically operate on serialized text, which may be a one-dimensional (JD) sequence of characters and words. While these methods have been successful documents having unformatted text (e.g., books, short text snippets), these methods have failed to capture the spatial and visual structure of the raw document. This failure to capture the spatial and visual structure has also become more apparent with the advent of new types of media and communication (e.g., websites, blogs, tables, presentations, and other formatted documents). The layout, positioning, and/or sizing of the content of a document may be crucial to understanding its semantic content. While human perception may be driven by the layout of a structured document, computer algorithms that rely on serialized text fail to adequately process structured documents when the relationship between words is impacted not only be the sequential order of the words but also by the document layout.
In the drawings, like reference numbers generally indicate identical or similar elements. Additionally, generally, the left-most digit(s) of a reference number identifies the drawing in which the reference number first appears.